As companies invest in Big Data
infrastructure they are looking for ways to show a return on that data.
Using business analytics to put this data to work improving
decision-making is central to success. But which decisions should be the
focus and how will you show improvement?

James
discussed the importance of improving day-to-day operational
decisions because of the largest scale and impact in front-line customer
interactions across multiple channels on the web, in email, on mobile, in
social, in call centers, in stores, in field sales or service.
Strategic and tactical decisions are made less frequently and
interactively and are riskier than front-line operational decisions where Big Data's velocity, volume, and variety is most relevant.

Key
to powering more proactive decisions with Big Data is reducing decision
latency from the time of an event to action with a better blend of
human and machine decision making. Low decision latency requires
automating front-line systems to be active participants, where as making
people only more analytical does not have as much impact on day-to-day
operations.

Begin with the outcome in mind then leverage Big Data in Decision Management Systems to test, learn, and adapt in production for quicker returns and better responses. Think
in probabilities for new customer demand in marketing and sales, for
reducing uncertainty, risk, and fraud in operations, and for improving
the experience in service and support. The opportunity to democratize
Big Data is in Little Decisions.